The optimum cultural conditions for garamicidin production by local isolate B.brevis were studied.Best result was obtained when the isolate B.brevis was grown on media composed of 1%glucose as carbon source,1% ammonium chloride as a nitrogen source ,0.5% Dipotassium hydrogen orthophosphate as a phosphate source and after 48 hours of incubation at 30C .Garamicidin has been extracted and purified through acid precipition and then extracted by organic solvent (ether& acetone ).Using HPLC the garamicidin antibiotic showed three types A,B and C garamicidin .

This study comprised three traverses extending parallel through the Northern, Central and Southern Mahmudiya districts, and perpendicular to the course of the Euphrates River. They were identified to collect (15) soil samples and some water samples as distributed within the land cover classes of the study area. Those classes were determined by visual interpretation and supervised classification for Landsat (TM) images obtained in August/2007. The digital classification was based on Maximum Likelihood method using six spectral bands excluding the thermal band. Chemical and physical laboratory analysis for the soil characteristics was performed to determine the types of land degradation in the study area.
The results showed that the hig

In the present research, the electrical properties which included the ac-conductivity (σac), loss tangent of dielectric (tan δ) and real dielectric constant (ε’) are studied for nano polycarbonate in different pressures and frequencies as a function of temperature these properties were studied at selective temperature gradients which are (RT-50-100-150-250)°C. The results of the study showed that the values of dielectric constant and dissipation factor increase with increasing pressure and temperature and decreases by increasing frequency. And the results of electrical conductivity showed that it increases with increasing temperature, pressure and frequency.

The present study aimed to evaluate the concentration of Malon dialdehyde (MDA) in pregnant women during different stages of pregnancy (stage of pregnancy, abortion, contraceptives and parity number).The study included (120) blood samples from normal pregnant women in age of the procreating were subdivided into three trimesters of pregnancy (40/group), and (40) samples from non-pregnant women as a control group. The results showed a significant increase in MDA in three stages of pregnancy compared with the control group. The concentration of MDA increased significantly in pregnant women with multipregnancy when compared with pregnant women for the first time, and in pregnant women whom was using contraceptions compared with p

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023